Development and validation of nomogram to predict very early recurrence of combined hepatocellular-cholangiocarcinoma after hepatic resection: a multi-institutional study

Wu, Yijun; Liu, Hongzhi; Zeng, Jianxing; Chen, Yifan; Fang, Guoxu; Zhang, Jinyu; Zhou, Weiping; Zeng, Yongyi; Liu, Jingfeng

doi:10.1186/s12957-022-02536-y

Cited by 10 publications

(8 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The presence of MVI more accurately predicted higher recurrence risk and poor clinical outcomes than factors included in the Milan criteria [ 6 ]. A nomogram containing MVI, macrovascular invasion (MaVI), and CA19-9 demonstrated favorable performance in predicting very early recurrence (recurrence within 6 months after surgery) in combined hepatocellular-cholangiocarcinoma after hepatic resection [ 10 ]. Moreover, MVI determines the risk for intrahepatic or distant dissemination of malignant cells, and MVI-positive HCCs should potentially be treated with a wider resection margin to eradicate micro-metastases compared with MVI-negative tumors [ 11 , 12 ].…”

Section: Introductionmentioning

confidence: 99%

Deep-learning-based analysis of preoperative MRI predicts microvascular invasion and outcome in hepatocellular carcinoma

Sun

Guan

et al. 2022

World J Surg Onc

View full text Add to dashboard Cite

Background Preoperative prediction of microvascular invasion (MVI) is critical for treatment strategy making in patients with hepatocellular carcinoma (HCC). We aimed to develop a deep learning (DL) model based on preoperative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to predict the MVI status and clinical outcomes in patients with HCC. Methods We retrospectively included a total of 321 HCC patients with pathologically confirmed MVI status. Preoperative DCE-MRI of these patients were collected, annotated, and further analyzed by DL in this study. A predictive model for MVI integrating DL-predicted MVI status (DL-MVI) and clinical parameters was constructed with multivariate logistic regression. Results Of 321 HCC patients, 136 patients were pathologically MVI absent and 185 patients were MVI present. Recurrence-free survival (RFS) and overall survival (OS) were significantly different between the DL-predicted MVI-absent and MVI-present. Among all clinical variables, only DL-predicted MVI status and a-fetoprotein (AFP) were independently associated with MVI: DL-MVI (odds ratio [OR] = 35.738; 95% confidence interval [CI] 14.027–91.056; p < 0.001), AFP (OR = 4.634, 95% CI 2.576–8.336; p < 0.001). To predict the presence of MVI, DL-MVI combined with AFP achieved an area under the curve (AUC) of 0.824. Conclusions Our predictive model combining DL-MVI and AFP achieved good performance for predicting MVI and clinical outcomes in patients with HCC.

show abstract

Section: Introductionmentioning

confidence: 99%

Deep-learning-based analysis of preoperative MRI predicts microvascular invasion and outcome in hepatocellular carcinoma

Sun

Guan

et al. 2022

World J Surg Onc

View full text Add to dashboard Cite

show abstract

“…Previous studies on early recurrence of HCC also highlight the independent influence of AST [27,28] and ALP [29,30] as contributing factors. Similarly, MVI has been established as a strong and independent predictor of early postoperative recurrence of cHCC-CC [12,13,15,22], likely because it is associated with the cytokines and proteins secreted by stromal cells in the tumor microenvironment that promote angiogenesis. MVI frequently involves small branches of the portal vein or hepatic vein, which results in early blood vessel dissemination.…”

Section: Discussionmentioning

confidence: 99%

“…Wu et al [22] used MiVI, MaVI, and CA19-9 > 25 u/ ml as independent risk factors for very early postoperative recurrence in cHCC-CC patients and constructed a nomogram model, with AUCs of 0.77 (95%CI 0.69-0.85) and 0.76 (95% CI 0.66-0.86) in the training set and validation set, respectively. Compared to that study, our study added CT features (included tumor size, tumor margin and arterial phase peritumoral enhancement) on the basis of clinical, pathological features, and the results improved the predictive power.…”

Section: Discussionmentioning

confidence: 99%

“…Furthermore, early recurrence, which mainly occurs within the initial two years after surgery and has a high recurrence rate of 57-75%, requires particular attention in cHCC-CC management [15-18, 20, 21]. A recent study developed a model for predicting very early recurrence (i.e., recurrence within 6 months after surgery) of cHCC-CC, However, it lacks preoperative imaging features, which is an important prognostic information [22].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Nomogram based on clinical and preoperative CT features for predicting the early recurrence of combined hepatocellular-cholangiocarcinoma: a multicenter study

Zheng,

Gu,

Huang

et al. 2023

Radiol med

View full text Add to dashboard Cite

Purpose To establish and validate a multiparameter prediction model for early recurrence after radical resection in patients diagnosed with combined hepatocellular-cholangiocarcinoma (cHCC-CC). Materials and methods This study reviewed the clinical characteristics and preoperative CT images of 143 cHCC-CC patients who underwent radical resection from three institutions. A total of 110 patients from institution 1 were randomly divided into training set (n = 78) and testing set (n = 32) in the ratio of 7–3. Univariate and multivariate logistic regression analysis were used to construct a nomogram prediction model in the training set, which was internally and externally validated in the testing set and the validation set (n = 33) from institutions 2 and 3. The area under the curve (AUC) of receiver operating characteristics (ROC), decision curve analysis (DCA), and calibration analysis were used to evaluate the model’s performance. Results The combined model demonstrated superior predictive performance compared to the clinical model, the CT model, the pathological model and the clinic-CT model in predicting the early postoperative recurrence. The nomogram based on the combined model included AST, ALP, tumor size, tumor margin, arterial phase peritumoral enhancement, and MVI (Microvascular invasion). The model had AUCs of 0.89 (95% CI 0.81–0.96), 0.85 (95% CI 0.70–0.99), and 0.86 (95% CI 0.72–1.00) in the training, testing, and validation sets, respectively, indicating high predictive power. DCA showed that the combined model had good clinical value and correction effect. Conclusion A nomogram incorporating clinical characteristics and preoperative CT features can be utilized to effectively predict the early postoperative recurrence in patients with cHCC-CC.

show abstract

“…In agreement with Saito et al [ 25 ], we found that the larger tumor size was associated with unfavorable outcomes. In addition, another study reported that the very early recurrence nomogram contained microvascular invasion, macrovascular invasion, and CA199 level [ 27 ]. In this study, we further stratified the AYA patients with the cutoff age of 30 years old and performed the survival analysis again.…”

Section: Discussionmentioning

confidence: 99%

Outcomes of adolescent and young patients with hepatocellular carcinoma after curative liver resection: a retrospective study

et al. 2022

View full text Add to dashboard Cite

Background The risk of HCC is documented to be age-related. The outcomes of young HCC patients on postoperative prognosis are not well understood. The study aims to compare the characteristic differences between adolescent and young (AYA) and non-AYA HCC patients. Methods We performed a retrospective analysis of the clinical and pathological findings and the survival of 243 HCC patients who underwent operations between 2007 and 2018. Results The AYA group had a higher AFP level and a higher prevalence of family history of HCC or other cancers than the non-AYA group (P < 0.01 and P < 0.05). AYA patients had more unfavorable pathological characteristics including bigger lesion size, microvascular invasion, portal vein invasion, and hepatic capsule invasion. They also had a more unfavorable Edmondson grade and less tumor capsule formation (P < 0.01). Age was an independent predictor of survival in HCC patients. AYA patients had poorer disease-free and overall survival than non-AYA patients did (P < 0.01). Patients under 30 years old had an even poorer disease-free survival than those aged 30–40 (P = 0.047). Conclusions AYA patients exhibited a higher recurrence rate and disease-related death rate with more unfavorable pathological characteristics. Enhanced follow-up for young HCC patients should be applied.

show abstract

Development and validation of nomogram to predict very early recurrence of combined hepatocellular-cholangiocarcinoma after hepatic resection: a multi-institutional study

Cited by 10 publications

References 41 publications

Deep-learning-based analysis of preoperative MRI predicts microvascular invasion and outcome in hepatocellular carcinoma

Deep-learning-based analysis of preoperative MRI predicts microvascular invasion and outcome in hepatocellular carcinoma

Nomogram based on clinical and preoperative CT features for predicting the early recurrence of combined hepatocellular-cholangiocarcinoma: a multicenter study

Outcomes of adolescent and young patients with hepatocellular carcinoma after curative liver resection: a retrospective study

Contact Info

Product

Resources

About